{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Extract Job Posts from Indeed"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Before extracting job posts from [Indeed](https://www.indeed.com/), make sure you have checked their [robots.txt](https://www.indeed.com/robots.txt) file. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create a table in database"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/ec2-user/anaconda3/envs/python3/lib/python3.6/site-packages/psycopg2/__init__.py:144: UserWarning: The psycopg2 wheel package will be renamed from release 2.8; in order to keep installing from binary please use \"pip install psycopg2-binary\" instead. For details see: <http://initd.org/psycopg/docs/install.html#binary-install-from-pypi>.\n",
      "  \"\"\")\n"
     ]
    }
   ],
   "source": [
    "import pandas\n",
    "import configparser\n",
    "import psycopg2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Read the database connection info from the config.ini"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "config = configparser.ConfigParser()\n",
    "config.read('config.ini')\n",
    "\n",
    "host = config['myaws']['host']\n",
    "db = config['myaws']['db']\n",
    "user = config['myaws']['user']\n",
    "pwd = config['myaws']['pwd']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Establish a connection to the databas, and create a cursor."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "conn = psycopg2.connect(host = host,\n",
    "                       user = user,\n",
    "                        password = pwd,\n",
    "                        dbname = db\n",
    "                       )\n",
    "cur = conn.cursor()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Design the table in SQL"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# replace the schema and table name to your schema and table name\n",
    "table_sql = \"\"\"\n",
    "            CREATE TABLE IF NOT EXISTS demo.indeed\n",
    "            (\n",
    "                id SERIAL,\n",
    "                job_title VARCHAR(200),\n",
    "                job_company VARCHAR(200),\n",
    "                job_loc VARCHAR(200),\n",
    "                job_salary VARCHAR(200),\n",
    "                job_summary TEXT,\n",
    "                PRIMARY KEY(id)\n",
    "            );\n",
    "\n",
    "            \"\"\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "create the table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "cur.execute(table_sql)\n",
    "conn.commit()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Request HTML\n",
    "\n",
    "[urllib.request](https://docs.python.org/3/library/urllib.request.html) makes simple HTTP requests to visit a web page and get the content via the Python standard library.\n",
    "Here we define the URL to search job pots about Intelligence analyst."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "url = 'https://www.indeed.com/jobs?q=intelligence+analyst&start=2'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "import urllib.request\n",
    "response = urllib.request.urlopen(url)\n",
    "html_data= response.read()\n",
    "#print(html_data.decode('utf-8'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Parese HTML\n",
    "We can use the inspector tool in browsers to analyze webpages and use [beautifulsoup](https://www.crummy.com/software/BeautifulSoup/bs4/doc/) to extract webpage data.\n",
    "pip install the beautiful soup if needed. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "!pip install beautifulsoup4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "from bs4 import BeautifulSoup\n",
    "soup = BeautifulSoup(html_data,'html.parser')\n",
    "#print (soup)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Use the <code> tag.find_all(‘tag_name’, tage_attr = ‘possible_value’)</code> function to return a list of tags where the attribute equals the possible_value.\n",
    "<ul>Common attributes include:\n",
    "<li> id</li>\n",
    "<li> class<span style =\"color:red\">_</span></li>\n",
    "</ul>\n",
    "\n",
    "<ul>Common functions include:\n",
    "<li> tag.text: return the visible part of the tag</li>\n",
    "<li> tag.get(‘attribute’): return the value of the attribute of the tag</li>\n",
    "</ul>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Since all the job posts are in the <code>div tag class = 'jobsearch-Sprep...'</code>, we need to find that div tag from the body tag."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "for table_resultsBody in soup.find_all('table', id = 'resultsBody'):\n",
    "    pass\n",
    "    #print(table_resultsBody)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "for table_pageContent in table_resultsBody.find_all('table', id = 'pageContent'):\n",
    "    pass\n",
    "    #print(table_pageContent)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "for td_resultsCol in table_pageContent.find_all('td', id = 'resultsCol'):\n",
    "    pass\n",
    "    #print(td_resultsCol)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Save Data to Database\n",
    "Now we find the div tag contains the job posts. We need to identify the job title, company, ratings, reviews, salary, and summary. \n",
    "We can save those records to our table in the database."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "#  identify the job title, company, ratings, reviews, salary, and summary\n",
    "for div_row in td_resultsCol.find_all('div', class_='jobsearch-SerpJobCard unifiedRow row result'):\n",
    "\n",
    "    # find job title\n",
    "    job_title = None\n",
    "    job_company  = None\n",
    "    job_rating = None\n",
    "    job_loc = None\n",
    "    job_salary = None\n",
    "    job_summary = None\n",
    "    for h2_title in div_row.find_all('h2', class_ = 'title'):\n",
    "       \n",
    "        job_title = h2_title.a.text.strip().replace(\"'\",\"_\")\n",
    "   \n",
    "    for div_dsc in div_row.find_all('div', class_ = 'sjcl'):\n",
    "        \n",
    "        #find company name\n",
    "        for span_company in div_dsc.find_all('span', class_ = 'company'):\n",
    "            job_company = span_company.text.strip().replace(\"'\",\"_\")\n",
    "        \n",
    "        # find location\n",
    "        for div_loc in div_dsc.find_all('div', class_ = 'location accessible-contrast-color-location'):\n",
    "            job_loc = div_loc.text.strip().replace(\"'\",\"_\")\n",
    "    \n",
    "    # find salary\n",
    "    for div_salary in div_row.find_all('div',class_ ='salarySnippet'):\n",
    "        job_salary = div_salary.text.strip().replace(\"'\",\"_\")\n",
    "    \n",
    "    #find summary\n",
    "    for div_summary in div_row.find_all('div', class_ = 'summary'):\n",
    "        job_summary = div_summary.text.strip().replace(\"'\",\"_\")\n",
    "        \n",
    "    # insert into database\n",
    "    \n",
    "    sql_insert = \"\"\"\n",
    "                insert into demo.indeed(job_title,job_company,job_loc,job_salary,job_summary)\n",
    "                values('{}','{}','{}','{}','{}')            \n",
    "                \"\"\".format(job_title,job_company,job_loc,job_salary,job_summary)\n",
    "\n",
    "    cur.execute(sql_insert)\n",
    "    conn.commit()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Query the Table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f528f9f30b8>"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df = pandas.read_sql_query('select count(*) as count,job_title from demo.indeed group by job_title order by count desc ', conn)\n",
    "df.plot.bar(x='job_title')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "cur.close()\n",
    "conn.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "conda_python3",
   "language": "python",
   "name": "conda_python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
